For the main visualization of the bias calculations (fig:application C), we employ a visual encoding similar to the well-known spreadsheets that decision makers currently use.
While this places them in a familiar environment, we have made several visualization adjustments to improve user guidance and bias discoverability.
To guide the user's attention within this visualization, annotations are automatically sorted by their bias value when selecting a metric filter, whereas sorting can be changed by the user.
This way, users can vertically scan the annotations visualization to compare different annotations with respect to a sensitive attribute direction, as the bars align vertically for each sensitive attribute direction [1]}, [2]} while preserving the common vertical scrolling direction for the list of attributes.
We additionally use color-coded bars for visualizing the correlation values, following Mackinlay's ranking [3]}, where color ranks just behind position for nominal data.
However, we employ position for the different metrics and labels to form a tabular display.
The length of these bars signals how strongly they correlate with a sensitive attribute direction, whereas the color is based on the direction of said correlation.
Here, positive correlations are visualized using a blue color scale, while negative ones are encoded using a red color scale.
